opencv

The OTB 3.18 release candidate 1 has been tagged, and is available for testing!

Some of the major changes in this release are:

Bridge to OpenCV classifiers: the architecture of the machine learning framework has been redesigned. It provides a simple and generic interface to create bridges with existing machine learning algorithms implementation. This new framework has been used to include OpenCV machine learning algorithms. So in addition to LibSVM, you can now use 8 other algorithms for your images classification tasks, such as bayesian, k-nearest neighbors, random forests, artificial neural network… All these classifiers can be reached directly from the TrainImagesClassifier and ImageClassifier applications (read this note to learn about migrating to these new applications).

Dempster-Shafer based fusion of classifications: A new method based on Dempster-Shafer theory has been developed to fuse multiple classification maps. This method will take advantage of the per-class strengh and weaknesses of each input classification (estimated from confusion matrices) to produce a robust output map combining the best of each input. It is available as an alternative choice to majority voting fusion in the FusionOfClassifications application.

Improvement of the StereoFramework application: a whole set of filters has been developed to enhance this application, including line-of-sight interesction, left-right / right-left coherency checking and fusion of several 3D clouds into one raster DSM. The application now allows to input several views of the same scene and build a single raster DSM from them combining the information from all pairs, which is most useful for tri-stereoscopic Pleiades data for instance.

Access to Gdal overviews and writing of output image subsets throughout the library using the box and resol parameters of the extended filenames.

There are a lot more new things coming with this release! For more information, please read the complete release note available here.